Positive and Negative Regression Candidates (2019 Fantasy Baseball)
We continue onwards and upwards with our players subjected to optimism or pessimism. Data continues to stabilize, meaning that strikeouts and walks are becoming more reliable, and we can begin to use other sabermetrics to at least get some ideas if certain players’ data back up their performance. There are lots of players to sort through, so let’s get right to it.
Negative Regression Candidates
Chris Bassitt (SP – OAK)
Not on anyone’s radar coming into the season, Bassitt has gained deep-league relevance. His 1.69 ERA, 29.9% K-rate, and 22.8% K-BB rate show a pitcher who has substantially improved. His K rate has risen nearly 10 percent, and his K-BB rate has improved exactly 12 percent. Based on these numbers, he has a solid FIP (3.69) and xFIP (3.35). He has gained some traction in ESPN leagues, up to almost 31% ownership. Strikeouts and walks are some of the earliest statistics to stabilize, so this could mean we are in line for a true breakout, right?
Wrong. Bassitt has a deep arsenal with a four-seamer, sinker, cutter, curve, and change. The cutter and sinker have seen decreased usage in favor of the four-seamer this year. The problem is the four-seamer simply isn’t that good. His four-seam fastball velocity ranks in just the 37th percentile, per Statcast. The spin rate percentile is even worse, so there’s not a lot of deception going on with it either. Hitters will stop whiffing at the slow fastball 17% of the time, and with no other pitch generating a whiff rate greater than a 15.7%, we should see the Ks come down. While an 11% swinging strike rate is solid, it does not support a 25% K rate, much less a 30% one.
With the strikeouts declining going forward, Bassitt will need to reduce his fly-ball rate, which ranks in the lower half of baseball. Historically, he has allowed more fly balls than league average, so we can’t assume he will adjust his batted-ball tendencies. I am expecting Bassitt to regress to the mean and be a blip on the radar when we look back at 2019.
Tommy La Stella (2B/3B – LAA)
I wrote a small blip about La Stella for my May update on exit velocity. Apparently, he didn’t read it — he’s continued hitting homers at a ridiculous pace. He’s also entrenched in the leadoff spot, as he’s hit there in his last six starts. Batting in front of Mike Trout is certainly good for his fantasy value, which has grown exponentially since the offseason.
La Stella’s exit velocity is still in the bottom 50 percent, and his hard-hit percentage ranks in the bottom 28 percent of the league. The primary reason La Stella has 11 bombs is due to a six-degree increase in launch angle, per Statcast. His average launch angle is just over 14 degrees, which is the ideal angle to swing for the fences. Of course, we can’t count on him maintaining a 28.2% HR/FB rate. His batted-ball tendencies are similar to last year, meaning that he still isn’t hitting enough fly balls to render 11 homers so far this year.
My oft-cited fantasy colleague Dan Richards recently came up with a “predicted homers” metric, meaning that we can reasonably calculate how many homers a player should have. Based on his barrels per plate appearance and expected slugging percentage, La Stella should have somewhere between five-six homers this year. He has solid plate discipline skills (3.4% swinging strike rate, 49.7% zone rate), so he is capable of hitting atop the lineup. But we can’t expect the power. A simple question: what happens when Justin Upton returns? Sell high on La Stella before you have to answer that question.
Ronny Rodriguez (2B/SS – DET)
Ronny Rodriguez seems to be the hitter’s version of Bassitt. Hitting six homers over 100 plate appearances and sporting a .271/.311/.615 slash line, he seems to be on the midst of a breakout.
Let’s dive deeper, starting with strikeouts and walks. His 24.3% K rate and 5.8% BB rate scream regression and a significant drop in his .280 average. Further, his 58.3% pull rate (per FanGraphs) suggests that he will be shifted on incessantly, thus reducing that average.
He seems to be crushing fastballs (.335 expected batting average) but is struggling on other types of pitches (.238 expected batting average on breaking balls, .188 on offspeed pitches). I am expecting pitchers to adapt to his weakness sooner rather than later. Rodriguez is a free swinger who chases 46.6% at balls outside the zone and sees just 37.4% of pitches in the zone. This has led to a 15.7% swinging strike rate, proving that the strikeout rate is no fluke.
The Tigers’ infield is clearly not that talented, but some configuration of Jordy Mercer, Jeimer Candelario, and Josh Harrison should end up playing more than Rodriguez in the long term (and maybe even near term).
Let It Ride
|Exit Velocity||Hard-Hit Rate||xSLG||xBA||xwOBA|
However, there are some signs under the hood that negative regression is coming, which is preventing me from buying high. Yes, Bell is in the midst of a breakout — there is no doubt about that. But it is nearly impossible (unless you are Christian Yelich or Mike Trout) to keep this up.
Some of those signs include his walk rate declining from 13.2% in 2018 to 10.6% through Monday. His O-Swing and O-Contact percentages both support a decline in walks. His strikeout rate is also up four percent, which is further supported by an increase in swinging-strike rate. He is swinging at strikes at a higher clip than last year, but making less contact on said strikes. Outside of balls and strikes, Bell has never posted a BABIP higher than .305, so I’m also expecting his current rate of .366 to come down, at least a little bit.
Let me be clear: I am not telling you to sell, unless the offer is for someone like Jose Ramirez. I am telling you that Bell is a strong hold, but buying high at this moment will likely leave you on the wrong side of the deal given that he is at his peak performance.
C.J. Cron (1B – MIN)
While not on the same level as Bell, Cron has had a great year in his own right. With 12 homers and a 123 wRC+, Cron is greatly surpassing expectations. His numbers are backed up by an average exit velocity in the 75th percentile and an expected slugging percentage in the 89th percentile. That exit velocity is up almost three miles per hour since 2018, and his barrel percentage ranks in the top seven percent of MLB. For good measure, the walk rate is up to league average, and his strikeout rate has dropped from 25.9% in 2018 to 21.3% in 2019. All this good stuff has happened despite just a .264 BABIP.
As with Bell, I am recommending a hold, but do not buy high. For one, there are playing-time concerns. Cron has never played more than 140 games in a season, which happened in 2018. He has been to the injured list twice, but the main reason for his lack of playing time is due to his general skill. Cron has always been a strikeout-prone player, hitting too many infield fly balls and not hitting the ball particularly hard. We have seen Cron perform at this level before, only to fall back to earth.
The projections have him hitting 30 dingers with 80-90 RBIs, which you will take from a corner infielder. Owned in just 42% of ESPN leagues, Cron is starting to garner standard 12-teamer relevance. If he is already owned, wait for him to cool off after his two-homer game to pounce.
Positive Regression Candidates
J.A. Happ (SP – NYY)
Happ struggled mightily against the Orioles on Monday, allowing six runs on nine hits over 3.2 innings. He struck out just three, and just 22% of his pitches went for whiffs or called strikes.
I’m going to chalk Monday’s bad outing up to the Orioles seeing him just five days ago. This is a great opportunity to buy low. After posting strikeout rates at 22.7% and 26.3% in 2017 and 2018, respectively, Happ’s 2019 rate sits at just 18.5. The drop in K rate seems to be directly coming from his fastball. His fastball velocity has seen a 20 percentile drop, and his fastball spin went from above average to below average year-over-year. Another issue with Happ is that while his fastball velocity has dropped, his changeup velocity has stayed the same. This creates a tunneling problem, meaning that there isn’t a large enough gap in velocity to keep hitters off balance.
The good news is that his barrel percentage and average exit velocity are the same as last year, and his swinging-strike rate is down from 10.4% in 2018 to 9.8% in 2019 — not the biggest deal, in the grand scheme of things. It at least says that his K rate is due for positive regression.
In short, Happ probably was not as good as his surface-level stats indicate in 2017 and 2018, nor is he as bad as he is currently pitching in 2019. Much like Kyle Hendricks, he is prone to a few bad outings if he is not able to keep hitters off balance. I’m expecting Happ’s ERA to hover around 4.00 with a 20-22% K-rate as a result of making adjustments to his fastball and changeup. Playing for the Yankees as they get healthy means that he will also pile up wins. You can probably trade for Happ after this outing for 25 cents on the dollar. Go do that.
Zack Wheeler (SP – NYM)
Wheeler is the poster boy for positive regression based on the gap between his ERA (4.85) and other ERA indicators such as FIP (2.86) and xFIP (3.50). He has been BABIP’d to death, seeing as there has been a 75-point increase between 2018 and 2019. The FIP is much lower as a result of allowing just four homers and posting a 26.2% K rate.
The issue with Wheeler stems from his control (8.6% walk rate, a full tick above last year) and increasing his sinker usage. Last year, he threw his sinker 15% of the time, which led to a .304 expected slugging. This year, he’s throwing it over 31% of the time, and the expected slugging is at .450. Sure, his ground balls are up with the sinker, but hitters are slugging just .219 against his four-seamer. Surprisingly, his usage on the pitch has decreased in tandem with his sinker. There is some contention between Brooks Baseball, Statcast, and FanGraphs regarding the usage of this pitch.
Regardless, I’m expecting Wheeler to find his groove and be a top-25 starting pitcher by the end of the year. He’ll get there by recognizing his need to adjust his pitch arsenal and find his control. His control is due for natural positive regression, given his increase in first-pitch strikes and an overall climb in pitches inside the zone.